In, for example, a production site and an elevator shaft, it is required to measure the dimensions of the working environment being a three-dimensional space for installation or maintenance of equipment. However, it is difficult to manually measure a three-dimensional space, and this difficulty frequently causes skipping of the measurement of a part or causes an error in some measured values. In such a case, correction in design, reprocessing of a member, or other such measure is required, which leads to a delay in work.
In addition, when an object of interest is owned by a customer, in order to remeasure the dimensions, it is required to again request the customer to stop the object at the site (for example, stop production or stop operating an elevator).
Against this backdrop, there has been a demand for measuring (scanning) the shape of a three-dimensional space in a simple manner and storing the three-dimensional shape, to thereby enable the dimensions of every part to be measured at any time and also enable a simulation of the installation to be verified.
As one method of acquiring the shape of the three-dimensional space, there is a method of manually scanning through use of a three-dimensional (3D) sensor. In this case, a feature is extracted from each of a plurality of pieces of measurement data. Then, the pieces of measurement data are subjected to registration so that the features observed in common between the pieces of measurement data overlap each other, to thereby create (update) a three-dimensional map. Such processing for the registration of pieces of data is called mapping.
In a related-art image processing device, a control unit includes a three-dimensional map generation unit. The three-dimensional map generation unit moves a camera and generates a partial three-dimensional map based on two two-dimensional images picked up at two spots. In addition, the control unit causes the camera to perform photographing from each of different spots on a guide rail, and generates and stores an entire three-dimensional map from the acquired image. Further, the control unit derives, based on the stored entire three-dimensional map, a spot from which a freely-selected image pickup target spot can be viewed without an obstruction. Then, in the vicinity of the derived spot, the control unit causes the camera to continue to pick up an image until a three-dimensional map including the image pickup target spot can be generated, and to generate the three-dimensional map of the part to acquire the three-dimensional map of the image target spot (see, for example, Patent Literature 1).
In another case, in a related-art self-position estimating method, a self position is estimated by detecting a feature point in an image picked up by an image capture device mounted to a mobile body and detecting the position of an object in the periphery of the mobile body from a change of the feature point on the image in accordance with the movement of the mobile body. At this time, when the mobile body is not rotating on the spot, the image pickup direction of the image capture device is set as an initial direction. Meanwhile, when the mobile body is rotating on the spot, the image pickup direction of the image capture device is set to be a direction that enables the pickup of at least a part of feature points existing in the image acquired before the mobile body rotates. With this setting, it is possible to reduce a probability of losing a feature point, and to continuously carry out self localization estimation (see, for example, Patent Literature 2).